In the burglary system, who is more reliable when a burglary happened??MARY or JOHN??Proof it by calculating using Bayesian Network.
Example (Pearl, 1988)
- You have a new burglary alarm at home that is quite reliable at detecting burglars but may also respond at times to earthquake. You also have 2 neighbours, JOHN and MARY, who promise you to call you at work when they hear the alarm. John always calls when he hears the alarm but sometimes confuses the telephone ringing with the alarm and call then. Also, Mary likes loud music and sometimes missed the alarm.
THE ANSWER :-
calculating using the Bayesian Network
After finished calculating by using the Bayesian Network, we can compare the value of P(J | B) with P(M | B).
JOHN = P(J | B) = 0.8490 (in the lecture slide)
MARY = P(M | B) = 0.6586
Therefore, we can conclude that JOHN is more reliable when a burglary happened.
In the burglary system, who is more reliable when a burglary happened??MARY or JOHN??Proof it by calculating using Bayesian Network.
Example (Pearl, 1988)
- You have a new burglary alarm at home that is quite reliable at detecting burglars but may also respond at times to earthquake. You also have 2 neighbours, JOHN and MARY, who promise you to call you at work when they hear the alarm. John always calls when he hears the alarm but sometimes confuses the telephone ringing with the alarm and call then. Also, Mary likes loud music and sometimes missed the alarm.
THE ANSWER :-
calculating using the Bayesian Network
After finished calculating by using the Bayesian Network, we can compare the value of P(J | B) with P(M | B).
JOHN = P(J | B) = 0.8490 (in the lecture slide)
MARY = P(M | B) = 0.6586
Therefore, we can conclude that JOHN is more reliable when a burglary happened.
- Syazwani Binti Hussen (22469)-